Criteria Air Pollutant and Greenhouse Gases Emissions from U.S.

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Energy and the Environment

Criteria Air Pollutant and Greenhouse Gases Emissions from U.S. Refineries Allocated to Refinery Products Pingping Sun, Ben Young, Amgad Elgowainy, Zifeng Lu, Michael Q. Wang, Ben Morelli, and Troy Robert Hawkins Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b05870 • Publication Date (Web): 03 May 2019 Downloaded from http://pubs.acs.org on May 4, 2019

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Criteria Air Pollutant and Greenhouse Gases Emissions from U.S. Refineries Allocated to

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Refinery Products

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Pingping Sun,a Ben Young,b Amgad Elgowainy,a * Zifeng Lu,a Michael Wang,a Ben Morelli,b

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Troy Hawkinsa

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a

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Illinois 60439, USA.

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b

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02421, USA.

Energy Systems Division, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont,

Eastern Research Group, Inc. (ERG), 110 Hartwell Avenue #1, Lexington, Massachusetts

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* Email: [email protected]

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Abstract

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Using Greenhouse Gas Reporting Program data (GHGRP) and National Emissions Inventory

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(NEI) data from 2014, we investigate U.S. refinery greenhouse gas (GHG) emissions (CO2, CH4,

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and N2O) and criteria air pollutant (CAP) emissions (VOC, CO, NOx, SO2, PM10, and PM2.5). The

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study derives (1) combustion emission factors (EFs) of refinery fuels (e.g., refinery catalyst coke

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and refinery combined gas); (2) U.S. refinery GHG emissions and CAP emissions per crude

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throughput at the national and regional levels; and (3) GHG and CAP emissions attributable to

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U.S. refinery products. The latter two emissions were further itemized by source: combustion

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emission, process emission, and facility-wide emission. We estimated U.S. refinery product GHG

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and CAP emissions via energy allocation at the refinery process unit level. The unit energy demand

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and unit flow information were adopted from the Petroleum Refinery Life Cycle

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Inventory Model (PRELIM V1.1) by fitting individual U.S. refineries. This study fills an

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important information gap as it (1) evaluates refinery CAP emissions along with GHG emissions;

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and (2) provides CAP and GHG emissions not only for refinery main products (gasoline, diesel,

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jet, etc.), but for refinery secondary products (asphalt, lubricant, wax, light olefins, etc.).

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1 Introduction

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Petroleum refining is central to the U.S. economy. In 2016, petroleum energy supplied ~36% of

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the total energy used in the United States[1] ~92% of U.S. transportation energy demand,[1] despite

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recent increases in the use of alternative transportation fuels. Petroleum refining is also ubiquitous

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in the supply chains of myriad products, While one of the most important industrial sectors to

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power the activities of modern society, the petroleum refining sector is also one of the main sources

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of air emissions and other environmental releases. For example, in 2016, the U.S. refining sector

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accounted for 3.1% of total U.S. carbon dioxide emissions.[2]

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For global and U.S. national interests, as well as efforts to reduce adverse environmental impacts

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from anthropogenic activities,[3] it is important to identify and quantify related emissions. Given

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the importance of curbing refinery air emissions, researchers have been striving to identify

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petroleum refinery emission sources, quantify the emission amounts, and benchmark emissions 3

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allocated to transportation fuels. These studies have mostly focused on GHG emissions, especially

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on carbon dioxide (CO2) emissions. For example, Furoholt (1995)[4] studied eight general refining

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processes in Norwegian refineries and applied a process unit level allocation method to calculate

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energy use and emissions for individual refinery products. Furoholt[4] demonstrated that using a

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process unit level allocation led to results significantly different from those obtained from

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aggregate refinery level allocation. Wang et al. (2004)[5] developed a petroleum refinery process

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based approach of allocating energy use in a refinery to individual products, based on shares of

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final and intermediate petroleum products (by mass content, energy content, or market value), as

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they flow through refining process units. They used results from a notional refinery to estimate

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process-level operations and energy burdens. Skone and Gerdes (2009)[6] allocated refineries’

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energy use and emissions to gasoline, diesel, and jet fuels applying (1) aggregate data from EIA

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on process unit throughput, and (2) aggregate inputs of 1996 data from an API/National Petroleum

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Refiners Association survey to vacuum distillation, hydrotreating, catalytic reforming, alkylation,

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and isomerization units. Bredeson et al. (2010)[7] described a refinery model in which individual

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process unit throughputs could vary without constraints, in order to determine key operational

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parameters for CO2 emissions. Their work revealed that the most important factor driving a

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refinery’s energy requirement is the hydrogen content of the products in relation to the content of

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the crude.

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More recently, the study by Elgowainy et al.[8] and Forman et al.[9] investigated U.S. refinery

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emissions allocated to refinery products by using linear programing (LP) modeling to model the

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operations of 43 U.S. refineries, representing 70% of the total U.S. refinery capacity. The results

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were then aggregated to present U.S. national average GHG emissions associated with various

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refinery products. In parallel, Abella et al.[10] created the Excel-based Petroleum Refinery Life4

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cycle Inventory Model (PRELIM) to track refinery energy uses and GHG emissions. PRELIM

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provides a transparent representation of intermediate flows among refinery process units and GHG

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emissions from those process units to allow users to configure refineries and estimate the

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associated GHG profiles for each product. Both research efforts assigned GHG emissions to

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refinery products based on intermediate flows. The studies of Elgowainy et al.[8] and Forman et

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al.[9] provide improved industry characterization using actual refinery configurations but at the

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expense of transparency, due to the confidentiality of the underlying data, while PRELIM provides

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full transparency with some loss in facility-specific fidelity. Cooney et al.[11] used PRELIM

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together with other models to quantify the life cycle GHG profile of U.S. refinery products in 2014,

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building on earlier efforts by Skone et al. (2009),[6] from the same research group.

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This study adds to these previous efforts by updating GHG emissions and expanding evaluation

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metrics by including criteria air pollutant (CAP) emissions, since CAP emissions are regulated

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under the Clean Air Act by the U.S. Environmental Protection Agency (EPA) to protect public

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health and welfare.[12] CAP includes nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2),

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particulate matter (PM), carbon monoxide (CO), and lead (Pb). In addition to these pollutants,

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emissions reductions of volatile organic compounds (VOCs) are important in reducing ground-

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level ozone.[12]

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This study covers six CAPs—VOC, CO, NOx, SO2, PM less than 10 μm (PM10), and PM less than

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2.5 μm [PM2.5])—and three GHG pollutants (CO2, CH4, and N2O), by using refinery-specific

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emissions reported to EPA datasets of the Greenhouse Gas Reporting Program (GHGRP)[2] and

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the National Emissions Inventory (NEI).[13] This work uses 2014 emissions inventory data and

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combines that with 2014 U.S. refinery capacity and refinery operations information to estimate 5

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emissions (1) released from refinery fuel combustions, (2) per crude processed in U.S. refineries,

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and (3) associated with each refinery product.

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This study covers more than 98% of existing refineries and fills an information and data gap by

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benchmarking national and regional CAP emissions for the production of a full slate of refinery

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products.

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While previous studies quantify GHG emissions attributed to the production of major refinery

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products,[8,10,11] the present study updates refinery GHG emission with additional values.

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1. This study estimates refinery GHG emissions allocated to not only major refinery products,

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but also secondary refinery products, lubricant, light olefins, asphalt, and wax. These

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results provide valuable information for assessing the environmental impacts of other

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industries, such as the pavement and construction industry (asphalt), petrochemical

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industry (light olefins), manufacturing industry (lubricant), and others.

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2. The GHG results can validate the methodology used for CAP emission studies, such as

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allocating refinery-reported facility emissions to refinery process units and product pools.

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Because there is no previously reported CAP data, it is essential to use this kind of

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methodology to validate the reliability of the reported results.

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3. The variations in refinery operations and resultant variations in emissions (by year, region,

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facility, emission control technology, and many other factors) justify reporting complete

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air emission information based on consistent operation and emission data and methodology

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(consistent year, region, facility coverage, etc.).

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Quantifying refinery emissions is important for understanding the supply chain environmental

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impacts of transportation fuels and a wide range of petroleum-derived chemicals.[14] These refinery

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onsite GHG and CAP emissions allocated to refinery products constitute key elements in

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establishing baselines of full life cycle evaluations of various refinery products. However, it is

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worth noting that the present study solely focuses on refinery onsite GHG and CAP emissions

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(within the refinery fenceline), with the boundary consistent with the GHGRP and NEI data set.

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The additional information needed for full life cycle analyses is extensive and far beyond the scope

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of this study, and thus is not included here.

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2 Methodology

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This study compiles comprehensive inventories of U.S. refinery emissions (reported by facilities

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and including detailed data from process units), and information about U.S. refinery operations,

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such as unit capacity, utilization rate, material and energy input, and final products. A rigorous

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refinery list matching was conducted to ensure the same refinery facility coverage among emission

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datasets and refinery production datasets, based on cross-checks of physical location, history of

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acquisitions/mergers, and capacity.

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Obtaining the GHG and CAP emissions associated with refinery products requires an appropriate

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allocation approach to attribute refinery facility and/or unit emissions to refinery final products.

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This allocation is enabled by using the Petroleum Refinery Life Cycle Inventory Model

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(PRELIM V1.1)[15] and fitting each individual refinery facility to one of the PRELIM V1.1

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configuration models. The modeling results are subsequently aggregated at the Petroleum

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Administration for Defense Districts (PADD) level and at the national level. The aggregation at

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the PADD level is set by data availability, because some data sources (e.g. refinery fuel 7

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combustion, refinery utilization rate, refinery net products) are only available at PADD or sub-

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PADD level.

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2.1 Data Sources

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This study used several datasets to establish GHG and CAP emissions for U.S. refineries. These

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datasets support facility and process level assessments of emissions as reported directly by

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facilities. Using facility level data and adjusting regional or national assessments of production

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and fuel consumption reduces the uncertainty that might arise from non-reporting facilities.

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CAP Emissions

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CAP emissions data come from the National Emissions Inventory (NEI) database, which provides

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emissions data for CAPs, criteria precursors, and hazardous air pollutants from U.S. point,

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nonpoint, on-road, off-road, and event sources.[13] The NEI database is updated every three years,

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and 2014 was the most recent year for which NEI data was available when the present work was

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pursued.[13] NEI emission records are reported using eight-digit Source Classification Codes

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(SCCs) that correspond to process units within a facility. In total, 128 refineries representing 99.3%

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of operating capacity were identified in the NEI for the year 2014.

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GHG Emissions

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The Greenhouse Gas Reporting Program (GHGRP) requires businesses operating in certain sectors

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to report their annual emissions of CO2, CH4, N2O, and certain fluorinated GHGs from specific

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equipment and processes at their plants.

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source that provides process level GHG emissions at refineries. Different sectors are regulated and

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subject to report under different subparts of the GHGRP. Petroleum refineries are regulated under

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Subpart Y, hydrogen facilities are regulated under Subpart P, and combustion emissions from any

[2]

The GHGRP represents the sole U.S. national data

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facility are regulated under Subpart C. Collectively, GHGRP data was identified for 137 petroleum

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refineries reflecting 98.7% of operating capacity in 2014.

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Facilities can report emissions using continuous emission monitoring systems or through specific

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emission calculation methods approved by the EPA. This variation in reporting approaches might

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result in variable accuracy of emissions from various facilities, units, or combustion fuels.

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GHG emissions are reported at the process level, varying significantly depending on the subpart,

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calculation method, and process type. Unlike the NEI, the GHGRP datasets do not include SCCs

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and do not use consistent field names across all records. Therefore, we use a combination of

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process text and subpart-specific details to categorize emissions to process units.

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Itemized Emissions

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Emissions can be itemized by three groups: process emissions, combustion emissions, and facility-

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wide emissions (FWE). Process emissions are those emissions solely sourced from and specific to

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certain refinery units (e.g., atmospheric distillation tower, alkylation unit), which are assigned to

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the appropriate units based on SCC or unit description. Combustion emissions are emissions from

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heat and steam generation; they result from the combustion of fuel to supply energy. FWEs are not

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specific to certain refinery conversion/separation process units; instead, they cover the emissions

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throughout the overall facility, such as the emissions from cooling water supply system, waste

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water treatment plant (WWTP), and flare, fugitive, tanker and other auxiliary processes. We

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allocated combustion and FWEs to refinery process units using the approach discussed in Section

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2.4.

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U.S. Refinery Fuel Consumption

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The U.S. Energy Information Administration (EIA) provides the fuel consumption of petroleum

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refineries, organized by PADD,[16] including refinery still gas, refinery catalyst coke, natural gas,

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and other fuels. The “other fuels” category includes “pentanes plus other hydrocarbons,

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oxygenates, hydrogen, unfinished oils, gasoline, special naphtha, jet fuel, lubricants, asphalt and

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road oil, and miscellaneous products.”[16] The portion of natural gas used as feedstock for hydrogen

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production[17] is excluded from the total natural gas (fuel) consumption at refineries. Table S1 in

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Supporting Information (SI) shows the facility coverage of each refinery fuel in the NEI and

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GHGRP dataset.

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The fuel volumes are converted to energy units using the lower heating value (LHV) of fuel

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provided by the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation

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(GREET®) model from 2016,[18] which is shown in Table S2 in the SI.

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To estimate fuel consumption consistent with the facilities for which emissions data are available,

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we scale fuel consumption by PADD based on the throughput of refineries that report emissions.

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(Table S3 shows adjusted fuel comsumptions to match the NEI dataset.) SI Tables S4 and S5 show

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the compiled GHG and CAP emissions from refinery fuel combustion in each PADD. In all cases,

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emissions data are available for facilities accounting for more than 95% of the PADD total crude

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inputs.

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Refinery Capacity and Throughput

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U.S. refinery capacity information is published annually in the EIA’s Refinery Capacity dataset,[19]

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and refinery capacity utilization is published for each sub-PADD district.[20] The refinery capacity

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utilization is used to calculate the actual crude processed at sub-PADD level. In 2014, 145 unique 10

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refineries were present across datasets. Of those, 124 were present across relevant datasets (EIA,

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NEI, and GHGRP), representing 98% of total operating capacity. Figure S3 in the SI shows a

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general unit process layout for a complex U.S. petroleum refinery.

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Refinery unit throughputs are calculated based on the capacity of each unit provided by the EIA

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Refinery Capacity dataset.[21] PADD sub-districts utilization rates are used to adjust unit

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throughput, because utilization rates by refinery and process unit are not available. Total operating

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capacity at each facility is calculated by subtracting idle capacity from operable capacity.[21] The

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unit throughput (Tu) for each unit at each refinery is calculated as shown below:

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𝑻𝒖 = 𝑼𝒏𝒊𝒕 𝑪𝒉𝒂𝒓𝒈𝒆 𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚

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(1)

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Unit charge capacity: Capacity of input feed to the refinery unit

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Operating capacity: refinery capacity in active operation, in barrels of crude oil input,

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Operable capacity: refinery capacity that is capable of active operation, including both operating

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capacity and idled capacity, in barrels of crude oil input.

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The unit throughputs, Tu, of each refinery can be aggregated to the national and PADD levels (see

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Table S13 in the SI).

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Refinery Product Outputs

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The EIA reports final refinery products in its net production at refineries dataset.[22] The EIA-

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reported refinery products are used as a reference to aid in allocating refinery emissions to

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products.

(

)

𝒃𝒃𝒍 𝑶𝒑𝒆𝒓𝒂𝒕𝒊𝒏𝒈 𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚 (𝒃𝒃𝒍 𝒑𝒆𝒓 𝒄𝒂𝒍𝒆𝒏𝒅𝒂𝒓 𝒅𝒂𝒚) × 𝑪𝒂𝒍𝒆𝒏𝒅𝒂𝒓 𝒅𝒂𝒚 𝑻𝒐𝒕𝒂𝒍 𝑶𝒑𝒆𝒓𝒂𝒃𝒍𝒆 𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚 (𝒃𝒃𝒍 𝒑𝒆𝒓 𝒄𝒂𝒍𝒆𝒏𝒅𝒂𝒓 𝒅𝒂𝒚) × 𝑼𝒕𝒊𝒍𝒊𝒛𝒂𝒕𝒊𝒐𝒏 𝒓𝒂𝒕𝒆 (%) × 𝟑𝟔𝟓

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2.2 Emission Factors Calculations

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In U.S. refineries, the combustion processes for energy supply drive a significant portion of

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refinery emissions. Emissions related to refinery fuel combustion are normalized to fuel use

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(dividing the amount of emission by the amount of fuel combusted) to develop fuel-specific

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combustion emission factors.

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The NEI database categorizes combustion emissions by fuel type (through combustion-related

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SCCs), including coal, distillate, liquefied petroleum gas (LPG), residual fuel oil, natural gas,

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refinery still gas, and other combustion fuels. Other combustion fuels include gasoline, jet fuel,

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and combustion of waste products.[13] Emissions produced by combustion for heat supply at

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specific refinery units such as fluid catalytic crackers (FCCs) are also categorized by fuel type.

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Flares are not included as fuel consumption because they are not a steady source of energy supply.

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Combustion emissions for each fuel are summed to the national or PADD level. Only facilities

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that match across NEI and EIA datasets are included in the emission aggregation.

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2.3 Refinery Emissions per Crude Throughput

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The refinery emission intensity per unit of crude throughput at the facility level can be derived by

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dividing the refinery facility emission amounts[2,13] by the refinery crude throughputs.[20,21] The

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emissions per crude input are also itemized to process emissions, combustion emissions, and FWEs.

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2.4 Refinery Emissions Allocated to Refinery Products

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Previous research efforts[23] have developed an approach to allocate the refinery facility and

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process emissions to individual refinery products at the refinery unit level by modeling refinery 12

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operations with LP modeling. Refineries use LP modeling to optimize refinery operations, which

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maximizes refinery profits. LP modeling is refinery-specific, and needs to be constructed based on

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very detailed refinery configurations. This information is often confidential, so constructing the

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LP models is often costly and time consuming. The present work executes unit-level allocations

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using PRELIM.[15] With built-in typical refinery configurations, PRELIM provides some typical

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energy flow and mass flow information that are sufficient to guide the process-unit-level allocation.

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PRELIM V1.1

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PRELIM is a life-cycle inventory spreadsheet that can model energy use and GHG emissions based

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on customizable crude assays and unit configurations. PRELIM has 10 built-in typical refinery

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configurations representing different refinery conversion capabilities: four simple configurations,

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three coking refinery configurations, and three hydrocracking refinery configurations[15] (units

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included are summarized in Table 2 in the PRELIM user manual).[24] In the present study,

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individual U.S. refinery operations in 2014 were modeled by fitting one of the PRELIM V1.1

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refinery configurations[15] with EIA-reported crude throughput. The strategy of matching

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individual U.S. refineries with PRELIM V1.1 configurations was adopted from previous research

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by Cooney et al. (2016).[11]

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PRELIM V1.1 requires crude slate specifications. Because individual refinery crude slates

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information is absent, the present study simplifies the crude slate by using one crude slate as

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surrogate for all individual refineries. The selected crude surrogate was West Texas Sour, with

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API 31.7–34.1° and a sulfur content of 1.28–1.31 wt%,[15,25] because it is used in U.S. refineries

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and is similar to the average crude API of 31.8 and sulfur content of 1.45 used in U.S. refineries

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in 2014.[26] The simplification of using one crude slate in the present study is expected to have 13

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limited impact on allocating refinery emissions to refinery products. This is because the present

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study does not model refinery emissions (i.e., create emissions data); instead, it allocates the

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known refinery emissions to refinery products by adopting the model energy flow information,

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which is dependent on configuration and independent of crude slates.[24]

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Refinery Unit Energy Intensity and Unit Energy Use

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Unit energy intensity values (fuel use, electricity use, and steam use) were developed based on

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values reported in PRELIM V1.1 and documented by Pellegrino et al.[27] and Szklo et al.[28] A

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boiler efficiency of 80% is assumed by adopting the value from the GREET 2016 model.

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Pellegrino et al.[27] provide values for additional units not included within PRELIM V1.1 (e.g.,

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lubricant production) and provides confirmation of reported energy demand. Table S14 in the SI

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shows the energy intensities of various refinery units.

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Most units obtain energy from the general heater and boiler system, and thus share emission

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burdens from refinery fuel combustion. However, there are some exceptions:

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FCC units often do not need heat or steam from the general heat and steam supply system.

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They are self-sufficient during process operation because they combust FCC catalyst coke

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during catalyst regeneration.[29]

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Fluid coker and flexi coker (there are only a handful of these units in U.S. refineries [21] as

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most coker units are delayed cokers) combust coke formed in process to supply energy. Thus,

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like FCC units, the fluid coker and flexi coker units do not demand energy from the general

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heat and steam supply system.

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Estimates of process unit energy intensity are combined with unit throughputs to estimate the total

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heat and steam demand in each refinery. The percentage share of energy uses for each refinery 14

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process unit can be calculated within each refinery and aggregated to national results, as shown in

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Table S15 in the SI. The resultant energy uses in individual facilities can be aggregated to the

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PADD and national levels, as shown in Table S16 in the SI. The refinery energy uses derived from

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unit energy intensity can be validated by comparing them with EIA reported energy uses (also

287

shown in Table S17 in the SI). The difference of only 2% energy use validates the present approach

288

to estimating unit energy use.

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Allocating Refinery Facility Emissions to Units

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The GHG and CAP emissions of individual refinery units can be categorized into three sources:

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process unit emissions, combustion emissions, and FWEs.

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Process emissions that NEI specifies for each unit are assigned to individual refinery process units

293

based on details provided in the NEI and GHGRP dataset.

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The combustion emissions from heaters and boilers are allocated to refinery process units based

295

on the units’ respective shares of each energy source (shown in Table S15 in the SI). This is

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because the GHGRP and NEI datasets do not specify combustion emissions related to each unit

297

from the facility-wide heat/steam system. This allocation is performed at each individual refinery

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to better reflect each refinery’s unit throughput and configuration.

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Some refinery FWEs — cooling tower, WWTP, and engines (mostly internal combustion engines),

300

categorized as FWE-1 — are also allocated to units based on the unit energy demand share

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(combined heat and steam demand). This is because these emissions are proportional to water use

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or engine use, which are in turn proportional to the process unit energy demand.[30] Other FWEs

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(fugitive, flare emissions, incinerator, tank, and others, categorized as FWE-2), do not correlate to

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unit energy use, and are allocated to refinery products directly based on the product energy content. 15

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The refinery unit GHG and CAP emissions (aggregated to the national level), after allocations of

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combustion emissions and FWE-1, are shown in Table S18 in the SI. The refinery GHG and CAP

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emissions are mainly sourced from the atmospheric distillation tower, catalytic reformer, FCC

308

unit, hydrogen plant, and hydrotreating units (for diesel, gasoline, naphtha, and gasoil). Note that

309

these units have different capacities, because they process different cuts (portions) of crude slates

310

and have differing prevalence in U.S. refineries. Considering the capacity factor, it is useful to

311

compare the unit emissions per unit throughput, or unit emission intensity, as shown in Table S19

312

in the SI. Accounting for the capacity difference of various refinery units shows that the most

313

emission-intensive units are the lubricant production, thermal cracking, alkylation, catalytic

314

reformer, and FCC units. This is expected, because these units are energy-intensive and thus bear

315

greater emission burdens from fuel combustion, consistent with previous research results.[8]

316

Refinery Product Outputs Modeling and Matching with EIA Reported Products

317

Products reported by EIA are matched to product categories in PRELIM V1.1 in order to relate

318

PRELIM-derived allocation factors to actual U.S. refinery products (see Table S21 in the SI). This

319

categorization matching is essential for an accurate allocation of refinery emissions to products,

320

because PRELIM V1.1 and the EIA report use somewhat different nomenclature.[22] Some

321

important variations are discussed in Section 5 in the SI. The model-derived refinery final products

322

show divergence (to various extents) from EIA reported products, due to deviations in refinery

323

configuration, operation, and various assumptions embedded in the model. The differences are

324

discussed in Section 6 in the SI.

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325

Allocating Refinery Process Unit Emissions to Final Products

326

Upon establishing the correspondence between PRELIM-derived products and EIA final products

327

(Table S21 in the SI), the factors for allocating refinery process unit emissions to refinery unit

328

products can be developed in PRELIM V1.1. These factors are calculated for each refinery facility

329

and aggregated at the PADD or national level based on a production weighted average. The

330

PRELIM V1.1–derived PADD and national unit allocation factors need some adjustments to better

331

reflect U.S. refinery productions. For example, a single PRELIM V1.1 final product (e.g.,

332

Jet-A/AVTUR) matches multiple EIA products (aviation gasoline, kerosene, naphtha), so further

333

allocation (splitting) is required to complete the allocation to EIA final products. Another example

334

concerns the burdens allocated to refinery still gas, which need to be reallocated to all other

335

products because refinery still gas is typically combusted onsite for energy supply. In particular,

336

the present study develops an original and important allocation method to allocate refinery

337

emissions to lubricant production (see Figure S6 in the SI), because PRELIM does not include

338

lubricant units. More details regarding EIA product splitting, refinery still gas emission burdens,

339

and lubricant production emissions appear in Section 7 in the SI.

340

Figure 1 summarizes the overall approach of allocating refinery facility emissions to refinery

341

products, mostly via unit-level allocation.

17

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342 343 344

Figure 1. Summary of How Refinery Emissions Are Allocated to Refinery Products (BOB refers to blendstock for oxygenate blending)

345

3. Results and Discussion

346

3.1 U.S. Refinery Fuel Combustion GHG and CAP Emission Factors

347

Figure 2 shows the shares of refineries GHG and CAP emissions in 2014 from the combustion of

348

various refinery fuels (the magnitudes of these emissions are provided in Tables S4 and S5 for

349

GHG and CAP emissions, respectively). At the national level, most combustion-related emissions

350

from refineries are from the use of refinery still gas and natural gas, followed by refinery catalyst

351

coke. Together, these account for between 91% and 100% of emissions across all pollutant species

352

tracked. The use of other fuels such as coal, distillate, and residual fuel oils varies across PADDs

353

but represents only a minor contribution to total emissions.

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354 355

Figure 2. Share of Combustion Emissions by Fuel Type for U.S. Refineries in 2014

356

As the dominant energy source, combined gas leads all criteria air pollutant emissions, especially

357

for VOC, CO, and NOx.

358

In the present study, the emissions from natural gas and refinery still gas are combined because it

359

is speculated that the consumption and emissions of two gases are not well differentiated in

360

refineries, which likely causes reporting inconsistencies in fuel consumption and combustion

361

emissions. Refinery still gas and natural gas are often used in the same combustion units at

362

refineries and the gas supply is adjusted depending on refinery and market conditions. Many

363

individual facilities do not report refinery still gas consumption or report no natural gas

364

consumption, both of which are unlikely. Furthermore, carbon dioxide releases from fuel

365

combustion should be consistent across all combustion technologies, based on the carbon content

366

of the fuel. However, carbon dioxide emissions estimates from reported natural gas combustion

367

are significantly lower than the normal range, while emissions from reported refinery gas

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368

consumption are significantly higher than the normal range, indicating some reporting errors

369

through mis-categorizating fuel types.

370

Emission factors by fuel type are calculated by dividing total emissions by total fuel consumption.

371

Emission factors are calculated for the fuels that are included in both the emission dataset and the

372

fuel consumption dataset, aggregated at the national and PADD levels. Table 1 shows GHG and

373

CAP emission factors for refinery catalyst coke in each PADD, and Table 2 shows the same for

374

refinery combined gas in each PADD. Tables S6 through S9 in the SI show the emission factor for

375

other fuels, distillate, “other” fuel, residual oil, and LPG. The emission factors for coal combustion

376

were only available for PADD 1. Therefore, the results are not shown as PADD comparisons, but

377

are listed later in the national average result.

378 379

Table 1. Emission Factors for Combustion of Refinery Catalyst Coke in U.S. Refineries in 2014 by PADDs , g/MJ for CO2 and mg/MJ for Other Pollutants Catalyst Coke Emission Factor (g/MJ for CO2 and mg/MJ for Other Pollutants) Pollutant

PADD 1

PADD 2

PADD 3

PADD 4

PADD 5

United States

CO2

98.2

99.7

91.3

98.9

104.5

95.9

CH4

3.7

3.1

2.8

3.5

3.0

3.0

N2O

0.7

0.6

0.6

0.6

0.6

0.6

VOC

0.4

2.7

2.2

4.8

2.5

2.3

CO

3.0

16.4

12.9

8.9

15.4

12.9

NOx

20.3

17.9

10.2

13.9

7.6

12.5

SO2

23.6

15.8

11.3

30.0

7.6

13.5

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Catalyst Coke Emission Factor (g/MJ for CO2 and mg/MJ for Other Pollutants)

380 381

Pollutant

PADD 1

PADD 2

PADD 3

PADD 4

PADD 5

United States

PM10

11.3

18.9

10.0

36.5

4.1

12.0

PM2.5

10.43

17.1

9.1

29.6

3.3

10.7

Table 2. Emission Factors for Combustion of Combined Natural Gas and Refinery Still Gas in U.S. Refineries in 2014 by PADD, g/MJ for CO2 and mg/MJ for Other Pollutants. Combined Gas Emission Factor (g/MJ for CO2 and mg/MJ for Other Pollutants) Pollutant

PADD 1

PADD 2

PADD 3

PADD 4

PADD 5

United States

CO2

56.8

56.6

58.5

63.9

56.2

57.7

CH4

2.9

3.1

3.5

3.8

2.5

3.2

N2O

0.6

0.6

0.7

0.7

0.5

0.6

VOC

1.2

2.3

2.2

2.9

3.2

2.4

CO

20.1

25.9

12.9

39.4

15.2

17.2

NOx

33.1

37.7

29.6

41.8

29.4

31.8

SO2

3.4

6.6

5.6

11.8

8.1

6.4

PM10

6.2

5.8

4.0

4.7

3.9

4.5

PM2.5

5.3

5.4

4.0

4.3

3.8

4.3

382 383

Refinery fuel emission factors vary significantly by fuel source and by PADD. Not only are they

384

determined by fuel properties (carbon density, sulfur content, heating values, etc.), they are highly 21

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385

affected by combustion technology/practice, emission control technology/practice, refinery

386

operations, and other factors. Relative to refinery combined gas, refinery catalyst coke typically

387

has lower emission factors for VOCs, CO, and NOx, but higher emission factors for SO2, PM10,

388

and PM2.5. These results reflect the PADD average emission conditions in 2014.

389

Refinery combined gas and catalyst coke are the main fuels used in refineries, producing 98% of

390

total refinery energy generated onsite. Their distinctive features (gas and solid state) differentiate

391

them from other fuels (liquid state) make them less prone to reporting errors by miscategorizing

392

fuel types. In addition, a high percentage of the emissions from coke combustion and refinery gas

393

combustion was reported based on measured data or process-specific considerations as opposed to

394

data calcuated with general formulas. All these factors contribute to robust and reliable emission

395

factor results for catalyst coke and refinery gas.

396

The CO2 emission factors of distillate, residual oil, other fuel, and LPG show some inconsistency

397

among PADDs, indicating the mismatch of GHG emissions data and fuel consumption data, likely

398

caused by reporting errors. However, it is worth mentioning that GHG emissions come from the

399

GHGRP database and CAP emissions come from the NEI database, and the two databases are

400

independent of each other. Therefore, the lower reliability of GHG emission factors of distillate,

401

residual oil, other fuel, and LPG does not indicate that CAP emissions are less reliable for these

402

fuels.

403

Comparison of Emission Factors with Other Data Sources

404

Emission factors for CAPs for each fuel type are compared to previously published emission

405

factors developed for AP-42 and GREET 2016

406

provides some default emission factors,[2] which are listed in Table 3 for comparison.

[18,31]

if they are available. The GHGRP also

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Table 3. Comparison of This Study’s Emission Factors, National Results Aggregated with Those from AP-42, GHGRP, and GREET (2016),g/MJ for CO2 and mg/MJ for All Others Pollutant

Present

AP42a

GHGRP

GREET

Present

AP42b

Catalyst Coke

GHGRP

GREETc

Combined Gasd

CO2

95

--

95

104

58

52

50

56

CH4

2.9

--

2.8

1.1

3.2

1.0

0.9

1.0

N2O

0.6

--

0.6

0.9

0.6

0.3

0.1

0.3

VOCs

2.3

--

--

0.5

2.4

2.4

--

2.4

CO

13.3

--

--

22.7

17.1

37.0

--

20.8–23.7

NOx

12.3

--

--

113.7

32.2

14.2–83.4

--

34.1–38.9

SO2

13.3

--

--

511.8

6.4

0.3

--

0.3

PM10

12.3

--

--

2.6

4.5

3.3

--

3.3

PM2.5

10.4

--

--

2.4

4.4

--

--

3.3

Present

AP42e

GHGRP

GREET

Present

AP42f

GHGRP

GREETg

Pollutant LPG

Distillate

CO2

4.4

63.5–72.0

58.7

64.4

123.2

70.1

70.1

73.0–73.9

CH4

0.2

1.0

2.8

1.0

4.8

--

2.8

0.19–4.0

N2O

0.0

4.5

0.6

4.5

0.9

--

0.6

0.6–0.9

VOCs

0.5

--

--

4.1

113.7

--

--

--

CO

0.9

--

--

3.3

246.4

407.6

--

19.9–625.6

NOx

3.5

--

--

65.4

691.9

--

--

51.2–1990.4

SO2

0.1

--

--

89.1

123.2

--

0.5

PM10

0.2

--

--

3.5

69.2

132.7

--

7.7–52.1

PM2.5

0.2

--

--

3.5

57.8

--

--

5.2–51.2

Present

AP42h

GHGRP

GREET

Present

AP42i

GHGRP

GREET

Pollutant Residual Oil CO2

68.2

--

70.1

Coal 80.5

142.1

91.0–123.2

88.1

94.7

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Pollutant

Present

AP42a

GHGRP

GREET

Present

AP42b

GHGRP

GREETc

CH4

2.7

--

2.8

3.0

17.1

0.19–15.2

10.4

1.1

N2O

0.5

--

0.6

1.6

2.5

0.6–1.5

1.5

0.8

VOCs

15.2

--

--

--

11.4

--

--

0.4

CO

78.7

15.2

--

34.1

142.2

9.5–208.5

--

22.7

NOx

436.0

30.3–170.6

--

132.7

350.7

132.7–587.6

--

113.7

SO2

398.1

436.0–483.3

--

644.5

1516.5

587.6–720.3

--

511.8

PM10

142.2

6.2–30.3

--

33.2

28.4

1.3–246.4

--

2.6

PM2.5

113.7

--

--

15.2

27.5

0.61–104.3

--

2.4

409

a. Catalyst coke EF is reported in AP-42 with different unit, g/m3 fresh feed.

410

b. Range of natural gas fired boilers.

411

c. Range of natural gas utility boilers.

412

d. The refinery fuel mix combustion emission factors are compared to the natural gas combustion emission factors.

413

e. Range of industrial and commercial boilers.

414

f.

415

g. Range of distillate fired boilers and diesel powered reciprocating engines.

416

h. Range of boilers for residual oil.

417

i.

Uncontrolled diesel engines.

Range of coal combustion boiler configurations; various control technologies may further reduce NOx, SO2, or PM.

418

AP-42[31] and the GREET model[18] cover a wide range of emission factors, reflecting the

419

variability of combustion technology, emission control technology, or fuel characteristics. Catalyst

420

coke is an important refinery fuel, but its emission factors are rarely reported, likely because the

421

catalyst coke is not recoverable in a concentrated form.[16] AP-42 reported catalyst coke emission

422

factor per cubic meter of feed. For comparison, the catalyst coke EF from the present study was

423

converted to the same unit and is shown in Table S10 in the SI. The comparison shows that the

424

present study’s EFs are one to three orders of magnitude lower than those of AP-42. The difference

425

might be caused by the changes in refinery operations and practices in the past decades, as the 24

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426

catalyst coke EF in AP-42 reflects refinery practices in 1960s–1970s,[31] while the results from the

427

present study reflect U.S. refinery practice in 2014. A study by Nelson and Nguyen[32] shows that

428

U.S. refinery CAP emissions decreased by 46–91% from 1990 to 2013 with the application of

429

emission control technologies. Another factor that could contribute to catalyst coke SO2 reduction

430

is the increased application of gas oil hydrotreating, which reduces the sulfur content of FCC unit

431

feedstock. From 1995 to 2014, U.S. national gas oil hydrotreating capacity increased by 45% to

432

2.9 million bbl/stream day.[33] GREET 2016[18] adopted the properties of petroleum coke to

433

estimate catalyst coke emission factors. It will likely overestimate the emission factors of catalyst

434

coke, because petroleum coke and catalyst coke are produced from different refinery reaction

435

processes (coker unit versus FCC unit) and using different feedstocks (vacuum residual oil versus

436

gasoil). The heavier and sourer vacuum residual oil (relative to gasoil) likely results in higher

437

carbon content and higher sulfur content in petroleum coke than in catalyst coke, leading to higher

438

combustion emission factors for petroleum coke.

439

The present study shows a higher combined gas CO2 emission factor than AP-42 and previous

440

GREET (2016) results because there is a higher carbon content in the ethane, and a higher share

441

of ethane in the refinery still gas than in the natural gas, which is primarily methane.

442

In the present study, LPG emission factors are very different from those of AP-42 and GREET.

443

Refineries do not commonly use LPG as a fuel (see Table S1). Therefore, emission factors derived

444

from its use in refinery operation are less representative, and might be more susceptible to reporting

445

errors. In particular, the very low CO2 emission factor from LPG indicates a low reliability.

446

The present study also shows a higher distillate CO2 emission factor than AP-42 or GREET 2016.

447

Comparing the difference in numbers of facilities reporting the use of distillate and the use of other 25

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448

fuels the NEI and GHGRP pools indicates that fuel type may have been mis-categorized for

449

distillate and other fuel (e.g., gasoline, jet) in GHGRP reporting. Meanwhile, the NEI dataset

450

includes 89 facilities that report distillate emissions. This makes the CAP emission factors more

451

reliable than GHG emission factors. The CAP emission factors estimated here are in line with

452

those reported by AP-42 and the GREET module.

453

The residual oil GHG and CAP emission factors from the present study are also in line with those

454

of AP-42 and GREET. This might be because residual oil is more distinguishable from other liquid

455

fuels used in refineries (distillate and other fuel), and thus less likely to be mis-categorized.

456

Overall, the major fuels used in refineries are catalyst coke and refinery combined gas. Together,

457

these account for more than 98% of the combustion energy generated onsite. The significant

458

facility coverage for catalyst coke and refinery combined gas (natural gas and still gas) make the

459

dataset less vulnerable to individual refinery reporting errors, which provides confidence in data

460

quality. The moderate facility coverage of residual oil use and distillate use in the NEI pool makes

461

the CAP emissions factors of these two fuels reasonably reliable. There are data inconsistencies

462

for the GHG combustion emission factors for LPG, distillate, and coal, indicating lower reliability.

463

3.2 U.S. Refinery CAP Emissions per Crude Throughput

464

The regional emissions by PADD per refinery throughput were investigated by dividing refinery

465

PADD-level emissions by PADD refinery crude throughput (that is equal to refinery operating

466

capacity multiply refinery utilization rates). Note that these values are not combustion factors of

467

crude oil; they are the overall refinery facility emissions averaged to crude throughput. Figure 3

468

shows the CAP and GHG emissions, and the data are also shown in Table S11 in the SI. 26

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469 470 471 472

Figure 3. Refinery CAP and GHG Emissions per Refinery Crude Throughput by PADD (The left y‒axis refers to mg CAP/MJ Crude and the right y‒axis refers to g CO2,eq/MJ crude).

473

Figure 3 shows that among the various PADDs, PADD 4 has the highest CAP emissions per unit

474

crude input. This is consistent with the fuel combustion results, which show that PADD 4 refineries

475

have higher CAP emission factors (for combined gas and catalyst coke) than the other PADD

476

refineries. In contrast to the trend of CAP emissions, the highest GHG emission per crude

477

throughput was observed for PADD 5. This is likely caused by the more complex refinery

478

configurations in PADD 5,[8] in response to processing heavy crude. The more complex refinery

479

configuration includes more process units that are often energy-intensive, which increases GHG

480

emissions. Note that CAP emissions do not necessarily track GHG emissions. Although CAP

481

emissions are largely related to combustion, environmental emissions are also influenced by

482

emission control technology, whereas CO2 emissions are determined by fuel properties in the

483

absence of carbon sequestration. 27

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484

Each PADD has different refining capacities, as shown in Table S12 in the SI. The contribution

485

of each PADD to national emissions, weighted by its capacity share, is shown in Figure S1 in the

486

SI. For all CAP and GHG pollutants, PADD 3 has the largest contribution of pollutant emissions,

487

because it has the largest capacity share (over 50% of national refinery capacity). Although PADD

488

4 has the highest emissions per unit of crude input, it only contributes a small portion of national

489

emissions, due to its small share in national refinery capacity (3.5%).

490

Note that emissions per crude throughput are not dependent on assumptions about crude slate or

491

refinery operations, because they are calculated based on GHG and CAP emissions reported to the

492

GHGRP and NEI, respectively, divided by crude throughput reported by EIA.

493

The present study shows that U.S. refineries have national average GHG emissions of 5.6 g

494

CO2,eq/MJ crude (5.0–7.1 g/MJ for various PADD refineries), consistent with the Abella and

495

Bergerson 2012[10] study. Abella and Bergerson[10] modeled GHG emissions by using PRELIM

496

V1.1 to simulate refinery processes with various configurations and operation scenarios. Among

497

the studied crude oils, the modeled GHG emissions were about 5.5–9.5 g/MJ crude for the

498

conventional crude oils with an API of 29.6–34.9° and sulfur content of 1.4–2.3 wt%. Note that in

499

2014, U.S. refineries used crudes with an average API of 31.8° and a sulfur content of 1.45 wt%;

500

the average properties are close to the properties of conventional crude oils.[26]

501

One study conducted for the American Fuel & Petrochemical Manufacturers organization by

502

Nelson and Nguyen[32] shows that NOx pollutant per crude input in refineries decreased to 100 g

503

NOx/m3 crude in 2011. The present study shows NOx emission of 2.32 g/MJ (84 g/m3) crude in

504

2014, comparable with the results from the Nelson and Nguyen study.

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505

Table 4 lists national emissions per crude processed in terms of process emissions, combustion

506

emissions, and FWEs (described in the Methodology section). The three emission shares from

507

each emission category are also shown in Figure S2 in the SI.

508

Table 4. U.S. Refinery GHG and CAP Emissions per Crude Throughput in 2014 Process Emissions 0.62

Combustion Emissions 4.84

Facility-wide Emissions 0.08

Total Emissions 5.54

CH4 (mg/MJ crude)

0.05

0.24

0.57

0.86

N2O (mg/MJ crude)

0.00

0.05

0.00

0.05

GHG (g CO2eq/MJ crude)

0.62

4.86

0.10

5.58

VOC (mg/MJ crude)

0.05

0.17

1.56

1.78

CO (mg/MJ crude)

0.05

1.09

0.39

1.53

NOx (mg/MJ crude)

0.04

2.00

0.29

2.32

SO2 (mg/MJ crude)

0.06

0.62

0.26

0.94

PM10 (mg/MJ crude)

0.02

0.43

0.18

0.63

PM2.5 (mg/MJ crude)

0.01

0.40

0.13

0.55

U.S. Weighted Average CO2 (g/MJ crude)

509 510

For most pollutants, such as CO2, N2O, CO, NOx, PM10, and PM2.5, the major source of emissions

511

is combustion. In contrast, CH4 and VOC emissions mainly come from FWEs. CH4 is mainly from

512

flare and fugitive emissions, while VOC is mainly sourced from fugitive and tank emissions.

29

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513

3.3 U.S. Refinery GHG and CAP Emissions per Refinery Product

514

With the refinery emission information and refinery products information, the GHG and CAP

515

emissions can be allocated to refinery products via the allocation approach described in Section 2,

516

by using PRELIM to implement unit-level allocation.

517

U.S. National Refinery Unit Emissions

518

Following the methodology summarized in Figure 1, the refinery emissions attributed to process

519

units are calculated. The national unit GHG and CAP emissions (including process emissions,

520

allocated combustion emissions, and allocated FWE-1 emissions) are listed in Table S18 in the SI,

521

and the unit emission shares are shown in Figure 4.

522 523 524 525

Figure 4. Shares of 2014 U.S. National Refinery Average GHG and CAP Emissions by Process Unit, After Allocations of Combustion Emissions andFWE-1, Based on Process Unit Heat and Steam Demand.

526

Refinery GHG and CAP emissions are mainly sourced from the atmospheric distillation tower,

527

catalytic reformer, FCC unit, hydrogen plant, and hydrotreating units (for diesel, gasoline, naphtha, 30

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528

and gasoil). These units have different capacities because they process different cuts (portions) of

529

crude slates and have different prevalence in U.S. refineries. For example, the atmospheric

530

distillation tower is present in every refinery and has the largest capacity, representing the overall

531

refinery crude process capability. In contrast, some other units, such as the coker and hydrocracker,

532

have smaller capacities because they process heavy cuts of refinery crudes and are often present

533

in more complex refineries. Considering these factors, it is useful to compare the unit emissions

534

intensity (dividing the total unit emissions by refinery unit throughput); the results are shown in

535

Table S19 in the SI.

536

Accounting for the capacity difference of various refinery units shows that the most emission-

537

intensive units are the lubricant production, thermal cracking, alkylation, catalytic reformer, and

538

FCC units. This is expected because these units are energy-intensive and thus bear greater emission

539

burdens from fuel combustion. This is consistent with previous research that indicated the

540

alkylation, catalytic reformer, and FCC units (the lubricant production and thermal cracking units

541

were not included in previous studies) are the leading refinery units in terms of GHG emissions[8,23]

542

and water consumption[30] (which is correlated to energy consumption). It is not surprising that the

543

lubricant production unit is very emission intensive because these processes are not only energy

544

intensive, and thus produce more combustion emissions, they also have high process VOC

545

emissions, likely due to solvent use and recovery.[29]

546

Refinery Final Products Derived from PRELIM V1.1

547

PRELIM V1.1 was used to model U.S. individual refinery operations (in 2014), using EIA-

548

reported crude input. The modeling of each refinery results in refinery final products based on

549

PRELIM refinery configurations. These model-derived refinery products amounts can diverge 31

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550

from the actual refinery products. Therefore, the model-resultant refinery final products are

551

compared to those of the EIA report, as described in Section 2; the results and discussions are

552

shown in Section 6 in the SI.

553

Refinery Emissions for Individual Refinery Final Products

554

The unit allocation factors to unit products (based on their energy contents), including still gas, are

555

shown in Figure S4 in the SI. As stated earlier, many units produce refinery still gas that is

556

subsequently combusted onsite to generate heat and steam. Emissions assigned to still gas from

557

each unit are pooled and reallocated to process units and subsequently to final products, based on

558

process unit heat and steam demand. The final allocation to units after the exhaustion of refinery

559

gas burdens is obtained after four iterations. The unit emissions after the reallocation of still gas

560

burdens are shown in Table S20 in the SI, and the unit allocation factors are shown in Figure S5

561

in the SI.

562

Combining the national or PADD refinery unit emission data with the refinery unit allocation

563

factors results in the emissions information for refinery products, including process emissions,

564

combustion emissions, and FWE-1, with still gas production burdens allocated to final products.

565

FWE-2 are allocated to final products based on their energy contents, independent of

566

PRELIM V1.1 use. Adding up the unit emissions attributed to refinery products and the FWE-2

567

attributed to refinery products produces the total emissions attributable to each refinery product.

568

The emissions allocated to each refinery product pool varies, and the shares of total facility

569

emissions are shown in Figure S7 in the SI. The emission contributions individual refinery

570

products make to total refinery emissions vary for each GHG or criterion pollutant. Gasoline BOB

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571

has the largest share for all pollutants, in the range of 47.7–57.9 wt%. Distillate/diesel has the

572

second largest share, in the range of 25.7–28.4 wt%.

573

Overall, dividing the refinery emissions allocated to refinery products (in kg/year) by refinery

574

products (in MJ) results in emissions per MJ of refinery product. The GHG and CAP emissions

575

for the production of refinery products are aggregated to the PADD and national levels. The

576

emissions associated with refinery products vary among PADDs, and the results are shown in

577

Table S24 in the SI. The comparison with literature data is shown in Figure S8 in the SI.

578

The emissions of the major refinery products—gasoline BOB, LPG, distillate, kerosene, and

579

residual fuel oil—are relatively consistent across all PADDs. In contrast, the less prevalent

580

products—lubricant, waxes, and miscellaneous products—show greater variation. The

581

miscellaneous products could include all finished products not classified elsewhere, such as

582

petrolatum, lube refining byproducts (aromatic extracts and tars), absorption oils, ramjet fuel,

583

petroleum rocket fuels, synthetic natural gas feedstocks, and specialty oils.[22] In the present study,

584

with the absence of sub‒category product information, the miscellaneous products are regarded as

585

aromatic extracts and tars from lubricant process. This is discussed further in Section 6 in the SI.

586

In particular, some GHG variations for lubricant, waxes, and miscellaneous petroleum products

587

can be attributed to the complex process of lubricant production, different sub-process units (e.g.,

588

hydrocracking versus solvent dewaxing), fewer datasets (e.g., PADD 2 has only one lubricant

589

production process), and the broad category of miscellaneous products, which impacts burden

590

allocation.

591

Combining the refinery emissions from each PADD produces the aggregate U.S. refinery GHG

592

emissions and CAP emissions, as shown in Figure 5. 33

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593 594 595 596 597

Figure 5. 2014 U.S. Refinery Onsite GHG Emissions and CAP Emissions Attributed to U.S. Refinery Products, National Aggregated Results (The left y‒axis refers to mg /MJ refinery product for CAPs and the right y‒axis refers to g CO2,eq/MJ refinery product for GHG).

598

In the present study, the GHG emissions and CAP emissions of gasoline BOB and LPG have

599

higher emissions than diesel/distillate, jet/kerosene, and aviation gasoline because the former two

600

are sourced from more energy-intensive conversion units (alkylation, catalytic reformer, FCC, etc.).

601

Unlike gasoline BOB, diesel is mainly produced from an atmospheric distillation tower, coker unit,

602

hydrocracker, and FCC. It is worth noting that diesel/distillate product has a sizeable CO2 emission

603

sourced from the hydrogen plant, owing to the extensive use of hydrogen for hydrotreating and

604

hydrocracking processes to produce clean (ultra-low sulfur) diesel (see Figure S9 in SI). Light

605

olefins have emissions similar to LPG, because they are mostly produced in parallel through a

606

series of conversion/separation units and treatment plants. The secondary refinery products,

607

lubricants, miscellaneous products, and wax have much higher emissions than the other refinery

608

products because they are produced from an energy-intensive lubricant production process. The 34

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609

detailed material and energy input attributed to each refinery product (upstream information) is

610

not investigated in the present study, as the present study solely focuses on refinery onsite

611

emissions.

612

The GHG emissions of the present study are also compared with those from previous research by

613

Elgowainy et al.,[8] Skone et al. (NETL report),[6] Cooney et al. (update of the NETL report),[11]

614

and PRELIM V1.1 results (those that were generated in our study during modeling of different

615

configurations), which are independent of NEI and GHGRP. These results are consistent, as

616

illustrated in Figure 6.

617 618 619

Figure 6. Comparison of U.S. Average Refinery Onsite GHG Emissions from this Study to Previously Published Research Results

620

The results from the present study match well with those of Elgowainy et al. [8] and are within the

621

low and high range of PRELIM V1.1. The Elgowainy et al.[8] study used LP modeling, a bottom-

622

up approach, to estimate refinery product GHG emissions for 70% of the U.S. refinery capacity.

623

The present study does not “create” refinery emissions by modeling, but instead allocates refinery-

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624

reported facility emission data to process units, then to refinery products, based on the refinery

625

unit energy use information from PRELIM V1.1.

626

Figure 6 shows that most refinery products have GHG emission values within the low and high

627

range of PRELIM V1.1 results, except for asphalt. This is probably because PRELIM V1.1 does

628

not include the lubricant production process and assumes that all asphalt comes from the asphalt

629

unit. In contrast, the present study assigns part of the lubricant production burden to a portion of

630

asphalt, which leads to higher asphalt GHG emissions because lubricant production is more

631

energy-intensive, and thus more GHG intensive, than asphalt units. The GHG emissions of

632

gasoline, diesel/distillate, and jet fuel/kerosene from the present study are lower than those of

633

NETL[6] and the research update by Cooney et al.[11] The following are some possible causes:

634

 First, the Cooney et al. study[11] used PRELIM V1.1 to model U.S. individual refinery

635

operations and fuel consumption and to generate emission data. Although the model adopts

636

typical conditions for U.S. operations, the process unit might have a different efficiency, as real

637

world refineries do,[24] which generally is optimized and associated with efficient recycling of

638

internal heat and steam. The deviation in process unit efficiency might lead to an overestimation

639

of fuel consumption and thus higher facility emissions and subsequently systematic higher

640

emissions allocated to all refinery products. In addition, the model does not “customize”

641

operations or processing based on crude slates, so all crudes are set to have the same

642

intermediate products. This could cause overestimated energy requirements for high-quality

643

crudes in more complex conversions,[24] resulting in overestimation of GHG emissions. In

644

contrast, the present study only attributes the known, refinery-reported facility or unit

645

emissions[2,13] to individual products. These emissions are actual emissions based on 2014 U.S. 36

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646

refinery operations. PRELIM V1.1 is not used to create GHG emission values based on fuels

647

use; it is used only to guide allocation.

648

 Second, the Cooney et al.[11] research does not include some secondary products (lubricant,

649

aromatics, wax, etc.). Thus, the burdens that should have been allocated to secondary products

650

shift to the main products (gasoline BOB, diesel/distillate, etc.), increasing the burdens on the

651

main products. In contrast, our study includes a more complete list of refinery products to share

652

the refinery operation burdens, leading to lower burdens for the main refinery products.

653

Note that the Cooney et al. research[11] used hydrogen allocation, while this study uses energy

654

allocation. The different allocation methods would change how the refinery GHG emissions are

655

attributed to the different refinery products, but would not alter the refinery overall GHG emissions.

656

Therefore, the different allocation methods are not the reason that the GHG emissions in the

657

Cooney et al.[11] study are systematically higher than those in the present study.

658

Unlike the research on the refinery products’ GHG emissions, research about the refinery products’

659

CAP emissions have rarely been reported. One conference paper (by the authors of the present

660

study)[34] summarized the allocation of individual refinery CAP emissions (from the 2014 NEI

661

database) to refinery products via LP modeling. That conference paper also reported the U.S.

662

national aggregate results derived from modeling 21 U.S. refineries (representing about 32% of

663

total U.S. refinery capacity in 2014). The comparison of current results with those of our previous

664

work using LP modeling are shown in Figure 7.

37

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665 666 667

Figure 7. Comparison of U.S. Average Refinery Product CAP Emissions from this Study to Sun et al. 2017[34] Derived from LP Modeling

668

In the Sun et al. 2017 work,[34] the CAP emissions of asphalt used the data for “heavy products.”

669

The heavy products category refers to miscellaneous final heavy products, which are specific to

670

individual refineries. It can include asphalt, light or heavy cycle oil, or heavy gas oil for sale.

671

Both sets of results are derived from the NEI dataset. This study uses PRELIM V1.1 as a platform

672

to execute the allocations. The previous study[34] used LP as a platform for allocation. Both results

673

show CAP emissions in the same order of magnitude, and there is good consistency for gasoline

674

BOB, diesel/distillate, jet/kerosene, residual fuel oil, petroleum coke, and asphalt. There is more

675

variation for the LPG and lubricant refinery products. In particular, the present study shows much

676

higher burdens for lubricant production than those derived from LP. The results of the present

677

study are expected to be more representative. This is because, relative to the results from LP

678

modeling,[34] the present study has more facility coverage with a higher production capacity (at the

679

national level), and conducts more accurate allocation due to the availability of energy uses of

680

lubricant production. 38

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681

The breakdown of the emissions associated with refinery products (U.S. average) is shown in

682

Table S25 in the SI. Consistent with the emissions per crude processed, for CO2, N2O, CO, NOX,

683

SO2, PM10, and PM2.5, most emissions are sourced from combustion. For VOCs and CH4, most

684

emissions are from FWEs.

685

The breakdown of the emissions associated with refinery products (U.S. average), by process unit,

686

are shown in Figure S9 to Figure S17 in the SI. The emission shares by process units vary

687

significantly with refinery product and pollutant type.

688

Future Work and Applications

689

The present study serves as an original exploratory work to develop a methodology and to

690

systematically benchmark U.S. refinery CAP emissions. Next efforts can focus on fine-tuning the

691

emissions allocated to refinery products by (1) modifying PRELIM V1.1 default configurations to

692

better match U.S. individual refineries, and (2) developing and using refinery specific crude slates

693

for individual refinery modeling.

694

The CAP and GHG emissions attributed to transportation fuels (e.g., gasoline BOB,

695

diesel/distillate and jet/kerosene fuel) can serve as air emissions baselines, against which the

696

environmental impact (CAP emission and GHG emission) of alternative transportation fuels

697

production (e.g., hydrogen production, biofuel production) can be evaluated. The CAP and GHG

698

emissions attributed to the production of some secondary products—such as asphalt, lubricant,

699

light olefins, wax, and others—fill a data gap for the quantitative analyses of air emissions

700

associated with basic materials manufacture, enabling the environmental evaluation of a number

701

of industries or industrial activities in modern society.

39

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702

In addition, the refinery process unit emission intensities are developed for GHG emissions and

703

CAP emissions. This information can be used to project future refinery emissions with varying

704

configurations and unit capacities, in response to ever-evolving energy landscape and fuel

705

regulations, volatile market demand, and many other factors. For example, EIA reports that since

706

2008, U.S. Gulf Coast refiners have shifted to lighter crudes due to the switch from heavier

707

imported crude to lighter domestic crude produced in Texas.[35] Meanwhile, EIA also reports that

708

PADD 2 refiners transitioned to heavier crudes[36] after 2010; this might be attributed to the

709

increased usage of discounted Canadian heavy oil. Regulatory driving forces also affect refinery

710

operations. For example, the upcoming International Convention for the Prevention of Pollution

711

from Ships (MARPOL) regulation,[37] which will come into effect in 2020, urges refineries to

712

provide low-sulfur marine fuels, which will likely result in increased usage of sweeter crude,[38] or

713

potentially drive refinery investment in unit additions or expansions (e.g., coker units).[39]

714

Meanwhile, the potential Reid Vapor Pressure waiver for E15 fuel

715

market shares for E15 fuel and subsequently refinery operations changes to reduce BOB volume

716

and produce different BOB recipes. These potential changes, along with other uncertain factors

717

not mentioned here, could profoundly influence refinery crude selection, operations adaptation, or

718

even configuration changes. In response to these dynamic changes, refineries will need to re-

719

optimize operations to maximize profits, which could increase or decrease energy use and

720

subsequent air emissions.

721

On the other side, refineries have succeeded in reducing air emissions significantly (especially for

722

NOx, SOx) in the past several decades, owing to the adoption of emission control technologies

723

(e.g., selective catalytic reduction (SCR) and ultra-low NOx burner) technology.[32] It is likely that

724

refineries will continue to curb air emissions (along with other environmental releases), driven by

[40]

could result in increased

40

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725

tightening regulations[38, 41] and economic gains from more efficient fuels use. The air emissions

726

reduction could be exercised by development in combustion control technology. For example,

727

recently one refinery in California adopted a new front-end fuel combustion technology that

728

reduced NOx emissions and CO emissions well below regional limits.[42] (Note that California is

729

among the regions with the most stringent regulatory requirements.) In addition, continuous

730

monitoring via more sensitive analytical instrumentation and responsive system controls of various

731

units (e.g., combustion, FCC unit, flare control, cooling tower, sulfur recovery unit, and so on),

732

could promote more efficient fuel combustion and mitigate process leak, thus reducing air

733

emissions.[43, 44]

734

Overall, the present study is the first, exploratory work to benchmark refinery CAP emissions

735

together with GHG emissions. The derived results of GHG and CAP emissions allocated to

736

refinery products establish baseline data to compare against future studies of refinery emissions

737

and against the environmental impacts of producing alternative or renewable fuels and chemicals.

738

In the future, a full life cycle analysis of various refinery products can be developed based on CAP

739

emission information for the recovery of various crude oils in conjunction with CAP emissions

740

measured for various refinery products applications, such as vehicle operations, asphalt for road

741

construction, olefins for petrochemical production and so on.

742

Supporting Information

743

Section 1: Additional information regarding facility coverage, energy uses used for investigating

744

the refinery fuels combustion emission factor, and emission factors for distillate, other fuel,

745

residual oil, and LPG. 41

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746

Section 2: Refinery emissions attributed to refinery crude throughput in each PADD.

747

Section 3: Calculations of U.S. refinery process unit capacity and energy use (heat, steam and

748

electricity), based on PRELIM modeling.

749

Section 4: Calculations of U.S. refinery emissions attributed to process units based on energy use

750

information

751

Sections 5 and 6: List of U.S. refinery products derived from PRELIM model and a comparison

752

with EIA report

753

Section 7: How unit emissions are attributed to unit products, especially for refinery still gas and

754

lubricant production processes.

755

Section 8: Air emissions attributed to individual refinery products produced in each PADD and

756

itemized by sources, emission type, and process units.

757

Acknowledgements

758

This research was supported by the Fuel Cell Technologies Office of the U.S. Department of

759

Energy’s Office of Energy Efficiency and Renewable Energy under Contract Number DE-AC02-

760

06CH11357. The authors are grateful to Fred Joseck from the U.S. Department of Energy’s Fuel

761

Cell Technologies Office for his guidance and support. The views and opinions of the authors

762

expressed herein do not necessarily state or reflect those of the United States Government or any

763

agency thereof. Neither the United States Government nor any agency thereof, nor any of their

764

employees, makes any warranty, expressed or implied, or assumes any legal liability or

42

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765

responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product,

766

or process disclosed, or represents that its use would not infringe privately owned rights.

43

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